I automate infrastructure and build AI tools: LLM inference on a single RTX 5090, agents with Claude Code, and the Proxmox and Docker stack they run on.
Stack
AI
LLM inference, CUDA, C++, AI agents, Claude Code, Cline, ChatGPT
Automation
Ansible, CI/CD, Docker, Git, Bash, PowerShell
Virtualization
Proxmox, VMware vSphere, HA clustering, Dell PowerEdge, NetApp, Backup
Microsoft
Entra ID, Intune, Active Directory, Exchange, SCCM, SQL Server, SharePoint
LLM server for NVIDIA Blackwell only (GeForce RTX 50, RTX PRO). On one RTX 5090, Qwen3.8-27B one user: 96.3 tok/s, 1.38x vLLM without speculative decoding, 1.23x llama.cpp on the same GGUF. Serves the 123.6 GiB Qwen3.8-Flash-Next from a 32 GB card at 92.1 tok/s. OpenAI and Anthropic API, tool calls, one docker run.
LLM server for AVX-512 (Zen 4/5, EPYC) and Arm Neoverse CPUs only. Ryzen 9800X3D prompt reading: 4.13x llama.cpp on Q8_0, 2.05x on Q4_K_M, same perplexity. Lossless speculative decoding, OpenAI and Anthropic API, one docker run.
Local-first AI prompt generator with a Gradio UI: 132 tuned roles for video, image, audio, 3D and creative AI tools. Runs uncensored Dolphin LLMs fully offline, auto-scaled to your GPU VRAM. No API keys, no cloud.
Rejection is the default: an operating manual for a Claude Code session whose job is driving other sessions and refusing anything not backed by evidence
Recover the CUDA launch and implicit-destructor edges a syntactic indexer loses, written straight into CodeGraph's SQLite graph. On imp (kekzl/imp, 240k lines of C++/CUDA): kernel launch coverage 74.2% → 99.3%, destructors 0% → 85%. On llm.c, which hides nothing, it adds 0 edges.
Monitor Entra ID (Azure AD) application secrets and certificates for expiration. Sends alerts via Email, Teams, Slack, or Webhook before credentials expire.
A living, continually learning neuromorphic being — a spiking neural network in C++23/CUDA with purely local plasticity (STDP, R-STDP, and Feedback Alignment instead of backprop). Runs on RTX 5090.